Install Syncopy#

Syncopy can be installed using conda:

We recommend to install SynCoPy into a new conda environment:

conda create -y --name syncopy python=3.8
conda activate syncopy
conda install -y -c conda-forge esi-syncopy

If you’re working on the ESI cluster installing Syncopy is only necessary if you create your own Conda environment.

Installing parallel processing engine ACME#

To harness the parallel processing capabilities of Syncopy it is helpful to install ACME.

Again either via conda

conda install -c conda-forge esi-acme

or pip

pip install esi-acme

Note

See Serial and Parallel Processing for details about parallel processing setup

Importing Syncopy#

To start using Syncopy you have to import it in your Python code:

import syncopy as spy

All user-facing functions and classes can then be accessed with the spy. prefix, e.g.

spy.load("~/testdata.spy")

To display your Syncopy version, run:

spy.__version__

Setting Up Your Python Environment#

On the ESI cluster, /opt/conda/envs/syncopy provides a pre-configured and tested Conda environment with the most recent Syncopy version. This environment can be easily started using the ESI JupyterHub

Syncopy makes heavy use of temporary files, which may become large (> 100 GB). The storage location can be set using the environmental variable SPYTMPDIR, which by default points to your home directory:

SPYTMPDIR=~/.spy

The performance of Syncopy strongly depends on the read and write speed in this folder. On the ESI cluster, the variable is set to use the high performance storage:

SPYTMPDIR=/cs/home/$USER/.spy